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In the development of various large-scale sensor systems, a particularly challenging problem is how to dynamically organize the sensor nodes into clusters and route the sensing information to a remote base station. By leveraging the spatial correlation, there have been some noteworthy clustering schemes proposed recently, such as EEDC and ASAP. However, they are based on an impractical assumption of single-hop network architecture, and the cluster construction communication cost is relatively high. With such motivation, the authors introduce a novel distributed clustering scheme to group the sensor nodes that have the highest similarity in observations into the same cluster and also construct a dynamic backbone of efficient data collection in wireless sensor networks.
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